Abstract: We introduce a new method for efficiently simulating liquid with
extreme amounts of spatial adaptivity. Our method combines several key
components to drastically speed up the simulation of large-scale fluid
phenomena: We leverage an alternative Eulerian tetrahedral mesh discretization
to significantly reduce the complexity of the pressure solve while
increasing the robustness with respect to element quality and removing the
possibility of locking. Next, we enable subtle free-surface phenomena by
deriving novel second-order boundary conditions consistent with our
discretization. We couple this discretization with a spatially adaptive Fluid-Implicit Particle (FLIP)
method, enabling efficient, robust, minimally-dissipative simulations that can
undergo sharp changes in spatial resolution while minimizing artifacts. Along the way,
we provide a new method for generating a smooth and detailed surface from a set
of particles with variable sizes. Finally, we explore several new sizing
functions for determining spatially adaptive simulation resolutions, and we
show how to couple them to our simulator. We combine each of these elements to produce
a simulation algorithm that is capable of creating animations at high maximum
resolutions while avoiding common pitfalls like inaccurate boundary conditions and
inefficient computation.
Ryoichi Ando, Nils Thürey and Chris Wojtan. ACM Tans. Graph. (SIGGRAPH 2013)